Wireless communication systems, including but not limited to, cellular systems, such as code division multiple access systems (CDMA) are known to use wireless receivers that employ variations of Weiner filter structures to compensate for channel related variations. Such channel variations can result in signal fading or multi-path signals that arrive at a receiver's antenna at different times depending upon their route from a transmitting antenna. As such, copies of the same signal may be received and are combined in a manner to improve received signal strengths. Channel equalizers, as known in the art, include filters that attempt to use energies of various copies to get a stronger signal. For example, approximations of Weiner filters are used in an attempt to correct for signal reductions and variations caused by channel conditions. As such Weiner filters are used to approximate an inverse of a channel's characteristics. As known in the art it is desirable to reduce errors of equalizers.
Also, for CDMA systems, it is known for example to use pilot sequences that are used to send known information so that a wireless receiver can determine channel characteristics. As such, wireless receivers are known to include a receiving antenna that is coupled to a radio frequency section which performs demodulation and other functions. The receiver may also include a square root raised cosine filter, a channel equalizer, a log likelihood ratio extraction circuit and a turbo decoder to decode received voice information. The channel equalizer circuitry may employ for example lattice multistage Weiner equalizers. The Weiner equalizers work in the time domain for example.
Chip level equalizers have been proposed for high speed downlink packet access as a mechanism of suppressing inter-code interference. By virtually restoring the orthogonality of the downlink channels, these chip level equalizers help avoid a main performance limitation of a RAKE receiver, and can dramatically improve system performance. A low complexity approximation to a Weiner filter would be useful.
FIG. 1 illustrates one example of a known channel equalizer 10 is operatively coupled to a receiving antenna 12 through one or more signal processing stages. As shown, a fast Fourier transform stage 14 changes the received wireless signal you into the frequency domain. The resultant received signal y(f) is then passed to a channel estimator circuit 16 which produces for example channel estimates for a group of chips represented as channel estimates PD 18. The received signal is also passed to an auto-covariance estimator 20 which produces data representing an auto-covariance matrix 22. The received signal is also buffered by buffer stage 24 until filter coefficients are determined. Buffer 24 may be a plurality of fast Fourier transforms as known in the art. The channel estimates 18 and the data representing the auto-covariance matrix 22 are received by a filter coefficient estimator 26 which may be, for example, a forward recursive covariance based coefficient generator, such as that described for example in an article entitled “Reduced Rank Adaptive Equalization”, authored by Yakun Sun, dated Jan. 30, 2001 which describes reduced rank adaptive space time equalization. Such coefficient generators generate filter coefficients 28 for an equalizer circuit 30 to suitably program the equalizer 30 (i.e. filter) to compensate for channel characteristics. Such coefficient generators are also sometimes referred to minimum mean squared error equalizer coefficient generators.
However, forward recursive covariance based coefficient generators typically require the calculation of normalized cross covariance vectors which when implemented in digital processors or other hardware, may be difficult to program. As such receivers may be more costly than necessary. In addition, such equalizer operations tend to operate in a forward recursion fashion only and can result in increasing vector sizes resulting from the numerous forward recursions.